PPT-Inference issues in OLS

Amine Ouazad Ass Prof of Economics Outline Heteroscedasticity Clustering Generalized Least Squares For heteroscedasticity For autocorrelation Heteroscedasticity Issue The issue arises whenever the residuals variance depends on the observation or depends on the value of the covariates. Ordinary Least Squares – a regression estimation technique that calculates the Beta-hats -- estimated parameters or coefficients of the model – so as to minimize the sum of the squared residuals.. rols. Carols. Carol. Carols. arols. rols. Carols. Carols. Carols. Carols. ols. Car. Carols. Carols. Carols. Carols. Carols. Carols. Carols. Carols. Carols. Carols. rols. Carols. C. a. r. o. l. s. . R. Session . 3 . – . Linear Regression. Amine . Ouazad. ,. Asst. Prof. of Economics. Econometrics. Session . 3 . – . Linear Regression. Amine . Ouazad. ,. Asst. Prof. of Economics. Outline of the course. Rahul Sharma and Alex Aiken (Stanford University). 1. Randomized Search. x. = . i. ;. y = j;. while . y!=0 . do. . x = x-1;. . y = y-1;. if( . i. ==j ). assert x==0. No!. Yes!.  . 2. Invariants. Protocols for Coreference Resolution. . . Kai-Wei Chang, Rajhans Samdani. , . Alla Rozovskaya, Nick Rizzolo, Mark Sammons. , and Dan Roth. . Chapter 14 . The pinhole camera. Structure. Pinhole camera model. Three geometric problems. Homogeneous coordinates. Solving the problems. Exterior orientation problem. Camera calibration. 3D reconstruction. What does it mean?. The variance of the error term is not constant. What are its consequences. ?. . Heteroscedasticity. does not destroy the . unbiasedness. and consistency properties of OLS estimators. Suhas Lohit, . Kuldeep. Kulkarni, . Pavan. . Turaga. ,. . Jian Wang, . Aswin. . Sankaranarayanan. Arizona . State . University. . Carnegie Mellon University. Sergio Pissanetzky. Sergio@SciControls.com. Emergent Inference. Any system. VISION. ROBOT. SOFTWARE. your mom. grab. an. object. computer. program. eyes. cameras,. sensors. translation. 100,000,000. Kari Lock Morgan. Department of Statistical Science, Duke University. kari@stat.duke.edu. . with Robin Lock, Patti Frazer Lock, Eric Lock, Dennis Lock. ECOTS. 5/16/12. Hypothesis Testing:. Use a formula to calculate a test statistic. Warm up. Share your picture with the people at your table group.. Make sure you have your Science notebook, agenda and a sharpened pencil. use tape to put it in front of your table of contents. Describe the difference between observations and inferences. Susan Athey, Stanford GSB. Based on joint work with Guido Imbens, Stefan Wager. References outside CS literature. Imbens and Rubin Causal Inference book (2015): synthesis of literature prior to big data/ML. An.  inference is an idea or conclusion that's drawn from evidence and reasoning. . An . inference.  is an educated . guess.. When reading a passage: 1) Note the facts presented to the reader and 2) use these facts to draw conclusions about . Chapter . 2 . Introduction to probability. Please send errata to s.prince@cs.ucl.ac.uk. Random variables. A random variable . x. denotes a quantity that is uncertain. May be result of experiment (flipping a coin) or a real world measurements (measuring temperature).